Radar Apparatus Resource Allocation for Adverse Weather Detection
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Solution Overview
Problem
Conventional light-based sensors, such as cameras and LiDAR, perform poorly in adverse weather conditions, limiting their reliability for autonomous perception and navigation in vehicles and robots.
Innovation Solution
The implementation of radar systems, including Frequency-Modulated Continuous Wave (FMCW) radar and Multiple-Input-Multiple-Output (MIMO) radar, which use radar signals to detect and analyze objects' range, speed, and angle of arrival, providing reliable data in various weather conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If light-based sensors (cameras, LiDAR) are used for autonomous perception, then measurement precision is improved under clear conditions, but reliability deteriorates in adverse weather conditions
Solution Approach 1:
The radar system is designed to perform multiple functions: it can detect objects in clear weather conditions and maintain reliable operation in adverse weather conditions such as rain, snow, and fog. This multi-functionality allows the same sensor system to replace or supplement light-based sensors across different environmental conditions, ensuring consistent autonomous perception capability regardless of weather.
2Reliability
If radar systems are implemented for adverse weather detection, then reliability is improved, but device complexity increases compared to conventional light-based sensors
Solution Approach 1:
The patent replaces complex mechanical sensor systems (cameras, LiDAR) with an electromagnetic wave-based radar system. This substitution eliminates the need for complex optical components, lenses, and mechanical scanning mechanisms while providing more reliable operation in adverse weather conditions. The radar system uses radio wave transmission and reception with signal processing to achieve object detection, simplifying the overall system architecture.
3Measurement precision
If FMCW radar and MIMO radar are used for enhanced object detection, then measurement precision is improved, but device complexity and energy consumption increase
Solution Approach 1:
The radar system divides the detection task into separate functional components: one or more transmit antennas for sending radar signals, one or more receive antennas for capturing reflected signals, and a processing unit for analyzing the signals. This segmentation allows each component to be optimized independently and enables flexible configuration to achieve precise range and speed measurements without requiring excessive complexity in any single component.
Solution Approach 2:
The FMCW radar uses periodic frequency modulation of the transmitted signal, sweeping through a frequency range over time. This periodic frequency variation allows the system to encode range information in the frequency domain and speed information in the Doppler shift, enabling precise measurements through systematic signal processing of the periodic waveforms.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables reliable object detection and navigation in adverse weather conditions, enhancing the performance of autonomous vehicles and robots by providing consistent sensor data independent of visibility.
Implementation Method 1
various types of radar, including Frequency-Modulated Continuous Wave (FMCW) radar and Multiple-Input-Multiple-Output (MIMO) radar, which use radar signals to detect and analyze objects
Implementation Method 2
transmitting a plurality of radar signals via a MIMO array formed by a plurality of transmit antennas and a plurality of receive antennas
Implementation Method 3
detect and analyze objects' range, speed, and angle of arrival
Data Source
AI summary
For example, a radar processor may include an input to receive radar Receive (Rx) information based on radar Rx signals received by a plurality of Radio Heads (RHs); and one or more Baseband (BB) Processing Units (BPUs) including a plurality of processing resources configured to generate radar information by processing the radar Rx information according to a plurality of BB-processing tasks. The one or more BPUs may be configured to allocate the plurality of processing resources to the plurality of RHs based on an RH to resource (RH-resource) allocation scheme. The RH-resource allocation scheme may be configured to define a plurality of RH-specific resource allocations for the plurality of RHs, respectively. For example, an RH-specific resource allocation for an RH may define a plurality of RH-allocated processing resources to perform the plurality of BB-processing tasks based on radar Rx information from the RH.